I'd like to go through each row in a pyspark dataframe, and change the value of a column based on the content of another column. The value I am changing it to is also based on the current value of the column to be changed.
Specifically, I have a column which contains DenseVectors, and another column which contains the index of the vector that I need.
Alternatively, I could also replace the DenseVector with the larger of the two values in the DenseVector.
I am mainly trying to use F.when() in conjunction with withColumn, but I am running into trouble with the second element of F.when(), as I want to store the correct index of the vector, but cannot directly index on a column.
a b 1 DenseVector([0.1, 0.9]) 1.0 2 DenseVector([0.6, 0.4]) 0.0 . . .
df = df.withColumn('a', F.when(df.b == 0.0, df.a) .otherwise(df.a)